Localizing Overlapping Parts by Searching the Interpretation Tree
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object recognition and localization via pose clustering
Computer Vision, Graphics, and Image Processing
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A new point matching algorithm for non-rigid registration
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Inkjet printed System-in-Package design and manufacturing
Microelectronics Journal
Half-tone perspective drawings by computer
AFIPS '67 (Fall) Proceedings of the November 14-16, 1967, fall joint computer conference
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Point pattern matching (PPM) is a widely studied problem in algorithm research and has numerous applications, e.g., in computer vision. In this paper we focus on a class of brute force PPM algorithms suitable for situations where the state-of-the-art methods do not perform optimally, e.g., due to point sets with regular structure. We discuss of an existing algorithm, which is optimal in the sense of brute force testing of different point pairings. We propose a parameter choosing scheme that minimizes the memory consumption of the algorithm. We also present a modified version of the algorithm to overcome issues related to its implementation and accuracy. Due to its brute force nature, the algorithm is guaranteed to return the best possible result.